WhatA platform that applies AI-powered vulnerability scanning specifically to legacy and unmaintained open-source projects that critical infrastructure depends on.
SignalThe discussion reveals broad agreement that AI can now find real vulnerabilities at scale, but the biggest unsolved problem is legacy systems that are difficult to patch — the long tail of critical but undermaintained code that large companies depend on but nobody audits.
Why NowFrontier AI models have demonstrably crossed the threshold of finding real zero-day vulnerabilities autonomously, but Anthropic is keeping the most powerful version internal — creating a capability gap that a focused startup could fill for the enterprise market.
MarketEnterprise security teams and government agencies; global application security market is ~$10B+ and growing fast; competes with Snyk, Semgrep, and traditional SAST/DAST but none apply frontier-model-level reasoning to legacy code at scale.
MoatAccumulating a proprietary vulnerability database and remediation patterns across legacy codebases creates compounding data advantages that new entrants cannot replicate.
Project Glasswing: Securing critical software for the AI eraView discussion ↗ · Article ↗ · 1,380 pts · April 7, 2026
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